1. Field of the Invention
The present invention relates to a method for the fast recognition of objects likely to form part of a collection comprising a large number of objects with different characteristics.
2. Description of the Prior Art
When objects of a same type, moving at high speed and in large numbers past a control station, have to be identified in order to be subsequently sorted out, the task of identification is generally performed by a human operator. To make it possible to automate an identification operation of this type, these objects have to be provided with a prior marking. This marking may be done, for example, by means of a bar code, as is being done already for mail sorting operations. To carry out this bar code marking speedily, in other words to justify the automation of the sorting operation, an operation of optic recognition has to be performed on the characters of the address written on a letter. This optic recognition is subject to high error rates if the address is handwritten. For example, as is shown in FIG. 1, an object 10 can move on a conveyor belt 20. This object 10 will have a bar code or similar readable marking 15 placed thereon, which can be read by ban optic recognition unit 25.
The objects to be identified may also be provided with "electronic labels", but this cannot always be done and may be too expensive if a large number of objects have to be sorted out.
Should the objects to be identified be differentiated by physical characteristics (such as dimensions, color, weight), electrical characteristics (such as dielectric permittivity), magnetic characteristics (such as permeance) or optic parameters (such as reflectivity, opacity etc.), a expert recognition systems may be used, but when these physical characteristics vary little from one object to another and/or when these objects file past swiftly and in large guantities, these expert systems are likely to be very complicated and costly.
When these objects are radars, some of whose technical parameters (transmission frequency, pulse width, scanning characteristics etc.) have been measured, the results of the measurements and of the analysis of their parameters have to be compared with a library of characteristics. This library contains a description of already identified radars (the description of which is known by other means), a and their modes of operation.
The known methods of identification of radars can be divided roughly into two main categories. The first category encompasses methods for comparing the variables measured with ranges (minimum, maximum) stored in a library, and for comparing discrete parameters. Such methods require the prior setting up of the libraries taking account of both the performance characteristics of the sensors that have given the variables measured and the ranges of variation of the parameters of the radars. Furthermore, these methods lead to the excessively severe exclusion of modes when the comparisons with the values of the libraries are not satisfactory, and this is the case chiefly for the secondary parameters and, above all, for the discrete parameters. In addition, these methods exhibit little flexibility in the weighting of the discriminating character of the different parameters. Furthermore, the digitization of the result is difficult. This is detrimental to the performance characteristics. It is also not possible to interpret the degree of confidence that is to be placed in the result.
The known systems belonging to the second category use powerful expert systems based on the principle of the enriching of a library as and when the results of measurements are acquired. This method has a very low speed of execution and its implementation requires very large-sized memories which may exclude its use in the case of on-board identification systems.